The present invention relates to a method and apparatus for reducing the effects of noise in a digital video system. In particular, low amplitude luminance components of a video signal are processed to reduce the relative intensity of noise, thereby resulting in improved image quality.
Generally, it is known that digital transmission of television signals can deliver video and audio services of much higher quality than analog techniques. Digital transmission schemes are particularly advantageous for signals that are broadcast via a cable television network or by satellite to cable television affiliates and/or directly to home satellite television receivers. It is expected that digital television transmitter and receiver systems will replace existing analog systems just as digital compact discs have replaced analog phonograph records in the audio industry.
A substantial amount of digital data must be transmitted in any digital television system. In a digital television system, a subscriber receives the digital data stream via a receiver/descrambler that provides video, audio and data to the subscriber. In order to most efficiently use the available radio frequency spectrum, it is advantageous to compress the digital television signals to minimize the amount of data that must be transmitted. Accordingly, various compression techniques have been developed which allow the processing of large amounts of data without significantly affecting the final quality of the displayed video image.
However, a significant amount of noise can be caused, for example, by quantization of a video signal. Quantization noise is introduced in digital communication systems when the number of bits used to represent a signal is reduced. For example, in a video transmitter, the maximum bit transmission rate is limited by the processing speed of various hardware components. Moreover, since the bit rate of data input to the transmitter may vary with time, the number of bits which can be allocated to represent the data can also vary. In particular, the use of compression techniques in video data processing can result in quantization error or noise that is relatively larger for low amplitude signals. That is, quantization noise can be more visible after performing spatial compression of portions of the image where the picture intensity (e.g., amplitude of the luminance component) is relatively low compared to the remaining portion of the image.
The presence of noise in the output of a digital video compression system tends to reduce the visual quality of images displayed, for example, at a television receiver. Moreover, this noise can be amplified by subsequent compression, transmission, reception and decompression processes. Previous methods to improve the image quality include an adaptive method, where more data bits are allocated to represent the low level luminance portions of an image. Other picture content-based adaptive compression techniques, such as increasing the picture bit rate of the compression system when low level luminance signals are detected, are also possible. However, these methods are inherently complex and require additional hardware to implement, thereby also driving up manufacturing costs. Moreover, the adaptive techniques are not easily used with different types of video signals.
Quantization is one form of compression that reduces the amount of data which is transmitted in a video system. Such quantization may be used with the well known Discrete Cosine Transform (DCT) to allow efficient transmission of digital video signals over conventional communication channels. The DCT transforms a block of pixels into a new block of transform coefficients. The transform is applied to each block until the entire image has been transformed. At the decoder, the inverse transformation is applied to recover the original image. The DCT merely transforms an image area from a fixed number of pixels to an equal number of transform coefficients. In order to compress the image, it is necessary to take advantage of an important property of the DCT. For typical images, a very large proportion of the signal energy is compacted into a small number of transform coefficients.
Coefficient quantization, or normalization, is a process that introduces small changes into the image in order to improve coding efficiency. This is done by truncating the DCT coefficients to a fixed number of bits. The truncation can be performed by shifting a coefficient from left to right and spilling the least significant bits off the end of a register holding the coefficient. In this way, the amplitude of the coefficient is also reduced. The number of bits used to represent each of the coefficients in the block of coefficients is assigned individually. The number of bits can be further reduced or increased as necessary to maintain a constant bit rate.
The most powerful compression systems not only take advantage of spatial correlation, but can also utilize similarities among adjacent frames to further compact the data. In such "motion compensation" systems, differential encoding is usually used to transmit only the difference between an actual frame and a prediction of the actual frame. The prediction is based on information derived from a previous frame of the same video sequence. Examples of video compression systems using the techniques of DCT quantization and motion compensation can be found in Krause, et al., U.S. Pat. Nos. 5,057,916; 5,068,724; 5,091,782; 5,093,720; and 5,235,419.
Moreover, in order to implement video compression in practical systems, a video decompression processor is required for each digital television receiver. Typically, filtering processes are performed at the receiver which correspond to the inverse of the filtering processes performed at the transmitter. In this way, the original data signal can be recovered. In particular, the development of very large scale integration (VLSI) integrated circuit chips is currently underway to implement such video decompression processors. However, in consumer products such as television sets, it is imperative that the cost of the system components be kept as low as possible.
It would be advantageous to reduce the effects of noise on a digital video signal, and particularly quantization noise that degrades low level luminance portions of an image, in order to improve image quality. In particular, a method and apparatus is needed that is relatively easy to implement yet still achieves the desired effect of masking noise at portions of a video image which have low amplitude luminance components. Moreover, it would be further advantageous to provide a system that is effective with different types of picture content.
The present invention provides a method and apparatus for reducing the effects of noise on a digital video signal which enjoys the above and other advantages.